Crowd noise is usually the primary noise in large waiting halls, and it is difficult to predict because it is influenced by several factors such as room acoustics and crowd characteristics. This study developed a crowd noise prediction model based on the superposition of direct and reverberant sound energy using the factors of the spatial layout of waiting halls, number and distribution of crowds, behavior ratio (ratio of vocal passengers to the total number of passengers), and average crowd sound power. To verify the model, on-site measurements were conducted in two large waiting halls to obtain the necessary input parameters. The crowd noise levels in one of the waiting halls were obtained from 1-s noise level data after excluding broadcast periods. A method for determining an individual's average sound power based on the model was also presented and found to be approximately 70.6 dB. Finally, the model was verified using measured data, and it showed that the model could accurately predict the average crowd noise level and changing trend of crowd noise in temporal and spatial dimensions with an average R-square of approximately 0.55 and average difference of approximately 1.1 dBA between the predicted and measured results.